In this paper, we study two estimation methods for the identification of aerodynamic parameters by using flight test data. One method is based on the Extended Kalman Filter(EKF) which treats the aerodynamic parameters as extra state variables. Another method is a two-step procedure, which uses state estimation for data smoothing and the least-squares estimation for parameter identification. The estimation accuracy of the two methods are compared by using simulated flight measurement data with various noise levels. And the latter method applied to 6-DOF aircraft motion to estimate the aerodynamic coefficients.
